ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · HANOVER, MA · 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/hanover/2022-annual-report
Yearly Traffic Safety Analysis
354 CRASHES IN
HANOVER, MA
2022
In 2022, Hanover recorded 354 total crashes, a 65.4% increase from the 214 crashes reported in 2021. While the number of fatalities remained constant at one death in each period, total injuries rose from 97 to 124. The most significant year-over-year change was the sharp rise in the overall number of collisions.
354
▲ 65.4%was 214
Total Crash Events
1
Persons Killed
124
▲ 27.8%was 97
Persons Injured
11
▲ 266.7%was 3
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash trends in Hanover show a significant year-over-year increase. Total crashes rose by 65.4%, from 214 incidents in 2021 to 354 in 2022. This upward trend is also reflected in the number of injuries, which increased by 27.8% from 97 to 124 over the same period.
11
Hit-and-Run Crashes — 2022
▲ 266.7% vs prior (3)
Hit-and-run incidents saw a substantial increase year-over-year. The number of hit-and-run crashes rose from 3 in 2021 to 11 in 2022. Consequently, the hit-and-run rate more than doubled, increasing from 1.4 per 100 crashes in 2021 to 3.1 per 100 crashes in 2022, indicating an upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
2
Pedestrians Injured
3
Cyclists Injured
119
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Tuesday with 62 incidents, a change from Thursday (38 crashes) in 2021. The peak hour also shifted slightly earlier, from 5 p.m. in 2021 (22 crashes) to 4 p.m. in 2022 (35 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the number of fatal crashes remained unchanged at one in both 2022 and 2021, the fatal crash rate per 100 crashes decreased from 0.47 to 0.28 due to the higher total crash volume. The proportion of crashes resulting in any injury (Serious, Minor, or Possible) decreased from 32.2% of all crashes in 2021 to 24.3% in 2022. Correspondingly, the share of non-injury crashes increased from 66.8% to 74.3% of the total.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
In both years, 'Failed to yield right of way' was the leading contributing factor, increasing in count from 70 crashes in 2021 to 116 in 2022, while its share of total crashes remained stable at approximately 32.8%. The second-ranked factor in 2022 was 'No improper driving' with 52 incidents, which was a 126% increase in count from 23 incidents in 2021. The count for 'Followed too closely' also rose from 31 to 39 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained broadly consistent year-over-year, with the majority of incidents in both periods occurring in daylight, on dry roads, and in clear weather. The proportion of crashes in daylight was 73.2% in 2022, compared to 72.4% in 2021. Similarly, crashes on dry roads accounted for 80.5% of the total in 2022 versus 80.8% in 2021, indicating no significant shift in the prevalence of adverse-condition crashes.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The ranking of top vehicle makes involved in crashes shifted, with Toyota becoming the most common make in 2022 with 112 vehicles, up from 53 in 2021 when it was ranked second. Ford, the top make in 2021 with 67 vehicles, was involved in 69 crashes in 2022. The number of people involved in crashes increased across all age groups, with notable growth in the 35-44 age group (from 57 to 115 people) and the 65+ age group (from 59 to 110 people).
Top Vehicle Makes (631 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
27 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (781 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes remained most prevalent in 35 mph and 40 mph speed zones in both years. The number of crashes in 40 mph zones increased from 69 in 2021 to 131 in 2022, while incidents in 35 mph zones grew from 68 to 93. The location of the single fatal crash shifted from a 45 mph zone in 2021 to a 40 mph zone in 2022.
Fatal crashes by zone: 40 mph: 1 of 131 (0.763%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.
Data Retrieval
- Access method: Arcgis_yearly Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: HANOVER, MA
- Total crash records analyzed: 354
- Total persons involved: 831
- Total vehicles involved: 631
Analytical Methodology
- Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
- Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
- Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
- Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
- Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
- Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
- AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.
Limitations & Disclaimers
- Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
- Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
- Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
- AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
- Percentages are calculated from reported data and are subject to rounding.
Non-Affiliation Disclosure
This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.
Data License
The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.
Corrections & Feedback
If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.
Suggested Citation
ThatCarHitMe.com (Injuria.ai). "HANOVER, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hanover/2022-annual-report
About the Publisher
ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.
Questions about this report's data or methodology: data@injuria.ai
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved